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[TensorV2] Multiply strided inputs and output #2434

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djeong20
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[TensorV2] Multiply strided inputs and output

This patch adds the implementation of multiplication operation that supports different strided inputs and output.

Self-evaluation:

  1. Build test: [X]Passed [ ]Failed [ ]Skipped
  2. Run test: [X]Passed [ ]Failed [ ]Skipped

Signed-off-by:Donghyeon Jeong [email protected]

[TensorV2] Additional functionality to access tensor elements

This commit adds functionality to retrieving and modifying tensor elements in specific locations.
This will provide convenience in implementing the math operation of tensor.

Self-evaluation:

  1. Build test: [X]Passed [ ]Failed [ ]Skipped
  2. Run test: [X]Passed [ ]Failed [ ]Skipped

Signed-off-by: Donghyeon Jeong [email protected]

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taos-ci commented Jan 29, 2024

📝 TAOS-CI Version: 1.5.20200925. Thank you for submitting PR #2434. Please a submit 1commit/1PR (one commit per one PR) policy to get comments quickly from reviewers. Your PR must pass all verificiation processes of cibot before starting a review process from reviewers. If you are new member to join this project, please read manuals in documentation folder and wiki page. In order to monitor a progress status of your PR in more detail, visit http://ci.nnstreamer.ai/.

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@djeong20, 💯 All CI checkers are successfully verified. Thanks.

return ((float *)getData())[i];
}

const float FloatTensor::getValue(unsigned int batch, unsigned int c,
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b,c,h,w or batch, channel, height, width ?

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b,c,h,w seems more reasonable.

* @brief return value at specific location
* @param[in] idx location
*/
const float getValue(unsigned int i) const noexcept;
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idx ?

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fixed!

This commit adds functionality to retrieving and modifying tensor elements in specific locations.
This will provide convenience in implementing the math operation of tensor.

**Self-evaluation:**
1. Build test: [X]Passed [ ]Failed [ ]Skipped
2. Run test:   [X]Passed [ ]Failed [ ]Skipped

Signed-off-by: Donghyeon Jeong <[email protected]>
This patch adds the implementation of multiplication operation that supports different strided inputs and output.

**Self-evaluation:**
1. Build test: [X]Passed [ ]Failed [ ]Skipped
2. Run test:   [X]Passed [ ]Failed [ ]Skipped

Signed-off-by: Donghyeon Jeong <[email protected]>
@djeong20 djeong20 force-pushed the impl/tensor_v2/multiply_strided branch from d4ab173 to c436e3c Compare January 30, 2024 01:32
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@djeong20, 💯 All CI checkers are successfully verified. Thanks.

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LGTM!

* @param[in] h height location
* @param[in] w width location
* @param[in] value value to be stored
* @param[in] beta scalar to multiply output with and add
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Just a suggestion:
How about describing params like beta something like:
x = x * beta + value for better intuition? Would it make doc more nasty?

for (unsigned int h = 0; h < height(); ++h) {
for (unsigned int w = 0; w < width(); ++w) {
output.addValue(
b, c, h, w, getValue(b, c, h, w) * m.getValue<_FP16>(b, c, h, w),
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do we need _FP16 in m.getValue? I thought we do not need to specify the type in TensorV2 level.

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We do. m is a TensorV2, not a HalfTensor, which means getValue is a Tensor::getValue that requires template argument.

for (unsigned int h = 0; h < height(); ++h) {
_FP16 *out_data = output.getAddress<_FP16>(b, c, h, 0);
const _FP16 *m_data = m.getAddress<_FP16>(b, c, h, 0);
const _FP16 *in_data = (_FP16 *)getAddress(getIndex(b, c, h, 0));
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Do we need the type casting for getAddress? This is HalfTensor->getAddress

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Yes. Since getAddress is an override method from TensorBase, it returns a void pointer, not _FP16 pointer.

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Do we need overwrite getAddress function from tensor base? How about add getAddress function without overwriting?

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We discussed offline and we will remove getAddress function in tensor_base.h later.

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@SeoHyungjun SeoHyungjun left a comment

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LGTM!

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LGTM

@jijoongmoon jijoongmoon merged commit 5e07bd1 into nnstreamer:main Feb 5, 2024
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@djeong20 djeong20 deleted the impl/tensor_v2/multiply_strided branch February 8, 2024 06:21
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6 participants